Java CSVLine.get方法代码示例

import de.linearbits.subframe.io.CSVLine; //导入方法依赖的package包/类
/**
 * Creates a series by selecting rows and taking three values
 * 
 * @param file
 * @param selector
 * @param xField
 * @param yField
 * @param zField
 */
public Series3D(CSVFile file, 
                Selector<String[]> selector, 
                Field xField, 
                Field yField, 
                Field zField){

    Iterator<CSVLine> iter = file.iterator();
    while (iter.hasNext()) {
        CSVLine csvline = iter.next();
        String[] line = csvline.getData();
        if (selector.isSelected(line)) {
            String x = csvline.get(xField.category, xField.measure);
            String y = csvline.get(yField.category, yField.measure);
            String z = csvline.get(zField.category, zField.measure);
            data.add(new Point3D(x, y, z));
        }
    }
}
 

import de.linearbits.subframe.io.CSVLine; //导入方法依赖的package包/类
/**
 * Creates a series by selecting rows and taking two values
 * 
 * @param file
 * @param selector
 * @param xField
 * @param yField
 */
public Series2D(CSVFile file, 
                Selector<String[]> selector, 
                Field xField, 
                Field yField){
    
    Iterator<CSVLine> iter = file.iterator();
    while (iter.hasNext()) {
        CSVLine csvline = iter.next();
        String[] line = csvline.getData();
        if (selector.isSelected(line)) {
            String x = csvline.get(xField.category, xField.measure);
            String y = csvline.get(yField.category, yField.measure);
            data.add(new Point2D(x, y));
        }
    }
}
 

import de.linearbits.subframe.io.CSVLine; //导入方法依赖的package包/类
/**
 * Analyzes the results from one experiment
 * @param file
 * @param measure
 * @param suppression
 * @param criterion
 * @throws ParseException 
 */
private static void analyze(CSVFile file,
                            BenchmarkQualityMeasure measure,
                            double suppression,
                            BenchmarkPrivacyModel criterion) throws ParseException {

    // Select
    Selector<String[]> selector = file.getSelectorBuilder()
                                      .field("Suppression limit").equals(String.valueOf(suppression)).and()
                                      .field("Quality measure").equals(measure.toString()).and()
                                      .field("Privacy model").equals(criterion.toString())
                                      .build();

    // Iterate
    for (Iterator<CSVLine> iter = file.iterator(); iter.hasNext(); ) {
        CSVLine line = iter.next();
        if (selector.isSelected(line.getData())) {
            double own = Double.valueOf(format(Double.valueOf(line.get("Lightning", Analyzer.VALUE)) * 100d));
            double datafly = Double.valueOf(format(Double.valueOf(line.get("DataFly", Analyzer.VALUE)) * 100d));
            double igreedy = Double.valueOf(format(Double.valueOf(line.get("IGreedy", Analyzer.VALUE)) * 100d));
            Object[] output = new String[]{criterion.toString(),
                                           line.get("", "Dataset"),
                                           format(own, own, datafly, igreedy),
                                           format(datafly, own, datafly, igreedy),
                                           format(igreedy, own, datafly, igreedy)};
            System.out.format("   - %-30s%-30s%-30s%-30s%-30s\n", output);
        }
    }
}
 

import de.linearbits.subframe.io.CSVLine; //导入方法依赖的package包/类
/**
 * Analyzes the results from one experiment
 * @param file
 * @param measure
 * @param suppression
 * @param criterion
 * @throws ParseException 
 */
private static void analyze(CSVFile file,
                            BenchmarkQualityMeasure measure,
                            double suppression,
                            BenchmarkPrivacyModel criterion) throws ParseException {

    // Select
    Selector<String[]> selector = file.getSelectorBuilder()
                                      .field("Suppression limit").equals(String.valueOf(suppression)).and()
                                      .field("Quality measure").equals(measure.toString()).and()
                                      .field("Privacy model").equals(criterion.toString())
                                      .build();

    // Iterate
    for (Iterator<CSVLine> iter = file.iterator(); iter.hasNext(); ) {
        CSVLine line = iter.next();
        if (selector.isSelected(line.getData())) {
            
            // Read values
            double _flash = getValue(line, "Flash", 1d / 1000d);
            double _lightning = getValue(line, "Lightning", 1d / 1000d);
            double _utility = getValue(line, "Quality", 100d);
            
            // Convert to strings
            String discovery = "--";
            String utility = "--"; 
            String flash = null;
            String lightning = null;
            if (_utility != -100d) {
                utility = format(100d - _utility);
                discovery = format(getValue(line, "Discovery", 1d / 1000d));
            }
            flash = format(_flash);
            lightning = format(_lightning);

            // Discovery and total time of lightning are potentially measured in different benchmark runs.
            // Due to fluctuations in the JVM execution times, discovery can thus be
            // a bit larger than total time, when they are actually identical. 
            // We handle this special case here.
            if (!discovery.equals("--") && Double.valueOf(discovery) > Double.valueOf(_lightning)) {
                discovery = format(_lightning);
            }
            
            // Print
            Object[] output = new String[]{line.get("", "Dataset"),
                                           flash,
                                           lightning,
                                           discovery,
                                           utility};
            System.out.format("%-30s%-30s%-30s%-30s%-30s\n", output);
        }
    }
}